Optimal timing of re-planning for head and neck adaptive radiotherapy.

BACKGROUND AND PURPOSE: Adaptive radiotherapy (ART) relies on re-planning to correct treatment variations, but the optimal timing of re-planning to account for dose changes in head and neck organs at risk (OARs) is still under investigation. We aimed to find out the optimal timing of re-planning in head and neck ART. MATERIALS AND METHODS: A total of 110 head and neck cancer patients were retrospectively enrolled. A semi auto-segmentation method was applied to obtain the weekly mean dose (Dmean) to OARs. The K-nearest-neighbour method was used for missing data imputation of weekly Dmean. A dose deviation map was built using the planning Dmean and weekly Dmean values and then used to simulate different ART scenarios consisting of 1 to 6 re-plannings. The difference between accumulated Dmean and planning Dmean before re-planning (ΔDmean_acc_noART) and after re-planning (ΔDmean_acc_ART) were evaluated and compared. RESULTS: Among all the OARs, supraglottic showed the largest ΔDmean_acc_noART (1.23 ± 3.13 Gy) and most cases of ΔDmean_acc_noART > 3 Gy (26 patients). The 3rd week is suggested in the optimal timing of re-planning for 10 OARs. For all the organs except arytenoid, 2 re-plannings were able to guarantee the ΔDmean_acc_ART below 3 Gy while the average |ΔDmean_acc_ART| was below 1 Gy. ART scenarios of 2_4, 3_4, 3_5 (week of re-planning separated with "_") were able to guarantee ΔDmean_acc_ART of 99 % of patients below 3 Gy simultaneously for 19 OARs. CONCLUSIONS: The optimal timing of re-planning was suggested for different organs at risk in head and neck adaptive radiotherapy. Generic scenarios of timing and frequency for re-planning can be applied to guarantee the increase of accumulated mean dose within 3 Gy simultaneously for multiple organs.

Challenges and opportunities for proton therapy during pregnancy.

During pregnancy, the use of radiation therapy for cancer treatment is often considered impossible due to the assumed associated fetal risks. However, suboptimal treatment of pregnant cancer patients and unjustifiable delay in radiation therapy until after delivery can be harmful for both patient and child. In non-pregnant patients, proton-radiation therapy is increasingly administered because of its favorable dosimetric properties compared with photon-radiation therapy. Although data on the use of pencil beam scanning proton-radiation therapy during pregnancy are scarce, different case reports and dosimetric studies have indicated a more than 10-fold reduction in fetal radiation exposure compared with photon-radiation therapy. Nonetheless, the implementation of proton-radiation therapy during pregnancy requires complex fetal dosimetry for the neutron-dominated out-of-field radiation dose and faces a lack of clinical guidelines. Further exploration and standardization of proton-radiation therapy during pregnancy will be necessary to improve radiotherapeutic management of pregnant women with cancer and further reduce risks for their offspring.

Assessment of residual geometrical errors of clinical target volumes and their impact on dose accumulation for head and neck radiotherapy.

PURPOSE: To assess the residual geometrical errors (dr) and their impact on the clinical target volumes (CTV) dose coverage for head and neck cancer (HNC) proton therapy patients. METHODS: We analysed 28 HNC patients treated with 70 Gy (RBE) and 54.25 Gy (RBE) to the therapeutic CTV70 and prophylactic CTV54.25, respectively. Daily cone beam CTs were converted to high quality synthetic CTs (sCTs). The CTVs from the nominal CT were propagated to the corresponding sCTs using a hybrid deformable image registration (propagated CTVs) in RayStation 11B. For 11 patients, all propagated CTVs were reviewed by our HNC radiation oncologist (physician corrected CTVs). The residual geometrical error dr was quantified as a function of the daily CTVs volume overlap with the nominal plan CTV. The errors dr(propagated CTVs) and dr(physician corrected CTVs) and the difference in dice similarity coefficients (ΔDSC) were determined. Using clinical plans, dose coverage and the tumor control probability (TCP) for the nominal, accumulated and voxel-wise minimum scenarios were determined. RESULTS: The difference in the residual geometrical error dr (propagated CTVs - physician corrected CTVs) and mean DSC (|ΔDSC|mean) were minor: Δdr(CTV70) = 0.16 mm, Δdr(CTV54.25) = 0.26 mm, |ΔDSC|mean < 0.9%. For all 28 patients, dr(CTV70) = 1.91 mm and dr(CTV54.25) = 1.90 mm. However, CTV54.25 above and below the cricoid cartilage differed substantially (1.00 mm c.f. 3.93 mm). The CTV54.25 coverage below the cricoid was then almost always lower, although the TCP of the accumulated dose was higher than the TCP of the voxel-wise minimum dose. CONCLUSIONS: Setup uncertainty setting of 2 mm is possible. The feasibility of using propagated CTVs for error determination is demonstrated.

An efficient strategy to select head and neck cancer patients for adaptive radiotherapy.

BACKGROUND AND PURPOSE: Adaptive radiotherapy (ART) is workload intensive but only benefits a subgroup of patients. We aimed to develop an efficient strategy to select candidates for ART in the first two weeks of head and neck cancer (HNC) radiotherapy. MATERIALS AND METHODS: This study retrospectively enrolled 110 HNC patients who underwent modern photon radiotherapy with at least 5 weekly in-treatment re-scan CTs. A semi auto-segmentation method was applied to obtain the weekly mean dose (Dmean) to OARs. A comprehensive NTCP-profile was applied to obtain NTCP's. The difference between planning and actual values of Dmean (ΔDmean) and dichotomized difference of clinical relevance (BIOΔNTCP) were used for modelling to determine the cut-off maximum ΔDmean of OARs in week 1 and 2 (maxΔDmean_1 and maxΔDmean_2). Four strategies to select candidates for ART, using cut-off maxΔDmean were compared. RESULTS: The Spearman's rank correlation test showed significant positive correlation between maxΔDmean and BIOΔNTCP (p-value <0.001). For major BIOΔNTCP (>5%) of acute and late toxicity, 10.9% and 4.5% of the patients were true candidates for ART. Strategy C using both cut-off maxΔDmean_1 (3.01 and 5.14 Gy) and cut-off maxΔDmean_2 (3.41 and 5.30 Gy) showed the best sensitivity, specificity, positive and negative predictive values (0.92, 0.82, 0.38, 0.99 for acute toxicity and 1.00, 0.92, 0.38, 1.00 for late toxicity, respectively). CONCLUSIONS: We propose an efficient selection strategy for ART that is able to classify the subgroup of patients with >5% BIOΔNTCP for late toxicity using imaging in the first two treatment weeks.

Proton therapy of a pregnant patient with nasopharyngeal carcinoma.

Background and purpose: Radiotherapy during pregnancy is rarely administered due to lack of data and practical challenges. This is the first detailed report of proton therapy as cancer treatment for a pregnant patient with nasopharyngeal carcinoma. Materials and methods: Pencil beam scanning proton therapy was prescribed to a pregnant patient to a total dose of 70 Gy (RBE) to the therapeutic CTV and 54.25 Gy to the prophylactic CTV, delivered in 35 fractions with a simultaneous integrated boost technique. Results: Phantom measurements showed a thirty-fold decrease in fetal radiation dose when using proton compared to photon therapy, with a total fetal dose of 5.5 mSv for the complete proton treatment, compared to 185 and 298 mSv for the photon treatment with and without lead shielding, respectively. After adminstering proton therapy during pregnancy, at 39 weeks of gestation, a healthy boy with a birthweight on the 83th percentile was delivered. Pediatric follow-up at 2 months of age of the offspring showed normal growth and age-adequate motor development with no signs of neurological problems. MR follow-up of the tumor 3 months after the end of treatment showed complete remission. Conclusion: This case demonstrates the potential of proton therapy for treatment during pregnancy.Compared to photon therapy, proton therapy can significantly limit fetal dose, while simultaneously offering a more optimized treatment to the patient.

Impact of sarcopenia on acute radiation-induced toxicity in head and neck cancer patients.

BACKGROUND AND PURPOSE: Sarcopenia is related to late radiation-induced toxicities and worse survival in head and neck cancer (HNC) patients. This study tested the hypothesis that sarcopenia improves the performance of current normal tissue complication probability (NTCP) models of radiation-induced acute toxicity in HNC patients. MATERIAL/METHODS: This was a retrospective analysis in a prospective cohort of HNC patients treated from January 2007 to December 2018 with (chemo)radiotherapy. Planning CT scans were used for evaluating skeletal muscle mass. Characteristics of sarcopenic and non-sarcopenic patients were compared. The impact of sarcopenia was analysed by adding sarcopenia to the linear predictors of current NTCP models predicting physician- and patient-rated acute toxicities. RESULTS: The cut-off values of sarcopenia in the study population (n = 977) were established at skeletal muscle index < 42.0 cm2/m2 (men) and < 31.2 cm2/m2 (women), corresponding to the lowest sex-specific quartile. Compared to non-sarcopenic patients, sarcopenic patients were more frequently smokers (61% vs. 48%, p < 0.001), had more often advanced stage of disease (stage III-IV, p = 0.004), higher age (67 vs. 63 years, p < 0.001) and experienced more pretreatment complaints, such as dysphagia (grade ≥ 2, p < 0.001). Sarcopenia remained statistically significant, next to the linear predictor, only for physician-rated grade ≥ 3 dysphagia (week 3-6 during RT, p < 0.01). However, sarcopenia did not improve the performance of these NTCP models (p > 0.99). CONCLUSION: Sarcopenia in HNC patients was an independent prognostic factor for radiation-induced physician-rated acute grade ≥ 3 dysphagia, which might be explained by its impact on swallowing muscles. However, addition of sarcopenia did not improve the NTCP model performance.

Evaluation of robustly optimised intensity modulated proton therapy for nasopharyngeal carcinoma.

BACKGROUND AND PURPOSE: To evaluate the dosimetric changes occurring over the treatment course for nasopharyngeal carcinoma (NPC) patients treated with robustly optimised intensity modulated proton therapy (IMPT). MATERIALS AND METHODS: 25 NPC patients were treated to two dose levels (CTV1: 70 Gy, CTV2: 54.25 Gy) with robustly optimised IMPT plans. Robustness evaluation was performed over 28 error scenarios using voxel-wise minimum distributions to assess target coverage and voxel-wise maximum distributions to assess possible hotspots and critical organ doses. Daily CBCT was used for positioning and weekly repeat CTs (rCT) were taken, on which the plan dose was recalculated and robustly evaluated. Deformable image registration was used to warp and accumulate the nominal, voxel-wise minimum and maximum rCT dose distributions. Changes to target coverage, critical organ and normal tissue dose between the accumulated and planned doses were investigated. RESULTS: 2 patients required a plan adaptation due to reduced target coverage. The D98% in the accumulated voxel-wise minimum distribution was higher than planned for CTV1 in 24/25 patients and for CTV2 in 20/25 patients. Maximum doses to the critical organs remained acceptable in all patients. Other normal tissue doses showed some variation as a result of soft tissue deformations and weight change. Normal tissue complication probabilities for grade ≥ 2 dysphagia and grade ≥ 2 xerostomia remained similar to planned values. CONCLUSION: Robustly optimised IMPT plans, in combination with volumetric verification imaging and adaptive planning, provided robust target coverage and acceptable OAR dose variation in our NPC cohort when accumulated over longitudinal data.

A novel semi auto-segmentation method for accurate dose and NTCP evaluation in adaptive head and neck radiotherapy.

BACKGROUND AND PURPOSE: Accurate segmentation of organs-at-risk (OARs) is crucial but tedious and time-consuming in adaptive radiotherapy (ART). The purpose of this work was to automate head and neck OAR-segmentation on repeat CT (rCT) by an optimal combination of human and auto-segmentation for accurate prediction of Normal Tissue Complication Probability (NTCP). MATERIALS AND METHODS: Human segmentation (HS) of 3 observers, deformable image registration (DIR) based contour propagation and deep learning contouring (DLC) were carried out to segment 15 OARs on 15 rCTs. The original treatment plan was re-calculated on rCT to obtain mean dose (Dmean) and consequent NTCP-predictions. The average Dmean and NTCP-predictions of the three observers were referred to as the gold standard to calculate the absolute difference of Dmean and NTCP-predictions (|ΔDmean| and |ΔNTCP|). RESULTS: The average |ΔDmean| of parotid glands in HS was 1.40 Gy, lower than that obtained with DIR and DLC (3.64 Gy, p < 0.001 and 3.72 Gy, p < 0.001, respectively). DLC showed the highest |ΔDmean| in middle Pharyngeal Constrictor Muscle (PCM) (5.13 Gy, p = 0.01). DIR showed second highest |ΔDmean| in the cricopharyngeal inlet (2.85 Gy, p = 0.01). The semi auto-segmentation (SAS) adopted HS, DIR and DLC for segmentation of parotid glands, PCM and all other OARs, respectively. The 90th percentile |ΔNTCP|was 2.19%, 2.24%, 1.10% and 1.50% for DIR, DLC, HS and SAS respectively. CONCLUSIONS: Human segmentation of the parotid glands remains necessary for accurate interpretation of mean dose and NTCP during ART. Proposed semi auto-segmentation allows NTCP-predictions within 1.5% accuracy for 90% of the cases.

Patient-Reported Toxicity and Quality-of-Life Profiles in Patients With Head and Neck Cancer Treated With Definitive Radiation Therapy or Chemoradiation.

PURPOSE: Radiation therapy is an effective but burdensome treatment for head and neck cancer (HNC). We aimed to characterize the severity and time pattern of patient-reported symptoms and quality of life in a large cohort of patients with HNC treated with definitive radiation therapy, with or without systemic treatment. METHODS AND MATERIALS: A total of 859 patients with HNC treated between 2007 and 2017 prospectively completed the European Organization for Research and Treatment of Cancer (EORTC) Quality of Life Questionnaire-Head and Neck Cancer module (QLQ-HN35) and Core Quality of Life Questionnaire (QLQ-C30) at regular intervals during and after treatment for up to 5 years. Patients were classified into 3 subgroups: early larynx cancer, infrahyoideal cancer, and suprahyoideal cancer. Outcome scales of both questionnaires were quantified per subgroup and time point by means of average scores and the frequency distribution of categorized severity (none, mild, moderate, and severe). Time patterns and symptom severity were characterized. Toxicity profiles were compared using linear mixed model analysis. Additional toxicity profiles based on age, human papillomavirus status, treatment modality, smoking status, tumor site, and treatment period were characterized as well. RESULTS: The study population consisted of 157 patients with early larynx cancer, 304 with infrahyoideal cancer, and 398 with suprahyoideal cancer. The overall questionnaire response rate was 83%. Generally, the EORTC QLQ-HN35 symptoms reported showed a clear time pattern, with increasing scores during treatment followed by a gradual recovery in the first 2 years. Distinct toxicity profiles were seen across subgroups (P < .001), with generally less severe symptom scores in the early larynx subgroup. The EORTC QLQ-C30 functioning, quality-of-life, and general symptoms reported showed a less evident time pattern and less pronounced differences in mean scores between subgroups, although differences were still significant (P < .001). Differences in mean scores were most pronounced for role functioning, appetite loss, fatigue, and pain. CONCLUSIONS: We established patient-reported toxicity and quality-of-life profiles that showed different patterns for 3 subgroups of patients with HNC. These profiles provide detailed information on the severity and persistence of various symptoms as experienced by patients during and after definitive radiation therapy. These profiles can be used to inform treatment of future patients and may serve as a benchmark for future studies.

Development of advanced preselection tools to reduce redundant plan comparisons in model-based selection of head and neck cancer patients for proton therapy.

PURPOSE: In the Netherlands, head and neck cancer (HNC) patients are selected for proton therapy (PT) based on estimated normal tissue complication probability differences (ΔNTCP) between photons and protons, which requires a plan comparison (VMAT vs. IMPT). We aimed to develop tools to improve patient selection for plan comparisons. METHODS: This prospective study consisted of 141 consecutive patients in which a plan comparison was done. IMPT plans of patients not qualifying for PT were classified as 'redundant'. To prevent redundant IMPT planning, 5 methods that were primarily based on regression models were developed to predict IMPT Dmean to OARs, by using data from VMAT plans and volumetric data from delineated targets and OARs. Then, actual and predicted plan comparison outcomes were compared. The endpoint was being selected for proton therapy. RESULTS: Seventy out of 141 patients (49.6%) qualified for PT. Using the developed preselection tools, redundant IMPT planning could have been prevented in 49-68% of the remaining 71 patients not qualifying for PT (=specificity) when the sensitivity of all methods was fixed to 100%, i.e., no false negative cases (positive predictive value range: 57-68%, negative predictive value: 100%). CONCLUSION: The advanced preselection tools, which uses volume and VMAT dose data, prevented labour intensive creation of IMPT plans in up to 68% of non-qualifying patients for PT. No patients qualifying for PT would have been incorrectly denied a plan comparison. This method contributes significantly to a more cost-effective model-based selection of HNC patients for PT.

First experience with model-based selection of head and neck cancer patients for proton therapy.

PURPOSE: In the Netherlands, head and neck cancer (HNC) patients qualify for intensity modulated proton therapy (IMPT) based on model-based selection (MBS). The aim of this study was to evaluate the first experience in MBS of HNC patients. METHODS: Patients who were subjected to MBS (Jan 2018-Sep 2019) were evaluated. A VMAT plan was created for all patients with optimal sparing of organ at risks (OARs) in normal tissue complication probability (NTCP) models for a number of toxicities. An IMPT plan was created only for those with NTCP difference (ΔNTCP) between VMAT and best-case scenario for proton (assuming 0 Gy dose for all OARs in IMPT plan) that exceeded any ΔNTCP-thresholds defined in Dutch National Indication Protocol. These patients qualified for a robust IMPT-plan creation with similar target doses and subsequent plan comparison. RESULTS: Of 227 patients, 141 (62%) qualified for plan comparison, of which 80 (35%) were eventually selected for proton therapy. Most patients were selected based on the ΔNTCP for dysphagia-related toxicities. The selection rate was higher among patients with advanced disease, pharyngeal tumors, and/or baseline complaints. A significant reduction in all OAR doses and NTCP values was obtained with IMPT compared with VMAT in both selected and non-selected patients, but more pronounced in patients selected for protons. CONCLUSION: Model-based selection of patients with HNC for proton therapy is clinically feasible. Approximately one third of HNC patients qualify for protons and these patients have the highest probability to benefit from protons in terms of toxicity prevention.